图学学报
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摘要: 针对传统图像匹配算法存在特征信息少和误匹配率高的问题,提出基于SURF 特 征提取和FLANN 搜索的图像匹配算法。通过Hessian 矩阵获取图像局部最值,并使用不同尺寸 特征描述器,同时处理尺度空间多层图像的向量特征,最后采用FLANN 搜索算法进行特征匹 配。试验表明,该算法比传统的图像匹配算法在效果和效率方面都表现得更好。
关键词: 加速鲁棒特征, Hessian, FLANN, 图像匹配
Abstract: The traditional algorithm of image matching exist the problems of little feature information and high rate false match. An image matching algorithm is presented based on SURF feature extraction and FLANN search. Firstly, the extremum value of local image is gotten using the Hessian matrix. Secondly, the feature vector is simultaneously processed in multilayer image scale space by using of different size feature description. Finally, the FLANN algorithm is used for feature matching. The experiments show that this algorithm is better than the traditional algorithm of image matching in the aspect of effectiveness and efficiency.
Key words: speed up robust features, Hessian, FLANN, image matching
冯亦东, 孙 跃. 基于SURF 特征提取和FLANN 搜索的图像匹配算法[J]. 图学学报.
Feng Yidong, Sun Yue. Image Matching Algorithm Based on SURF Feature Extraction and FLANN Search[J]. Journal of Graphics.
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http://www.txxb.com.cn/CN/Y2015/V36/I4/650